1. Field of the Invention
The present invention generally relates to engineering and management systems for the design and on-going operation of wireless and wired communication networks or systems and, more particularly, to a method for determining and maintaining the proper configuration of wireless or wired network hardware in terms of power output, gain, attenuation, channel, frequency settings, throughput settings, antenna positioning or adjustments, adaptive control of transmission or reception parameters, adaptive control of coverage zones, handoff zones, user quality of service, overall performance of a class of users, in any environment (e.g., buildings, floors within a building, campuses, within cities, an outdoor setting, etc.) in order to achieve some optimal or preset or desired performance goals (e.g., signal-to-interference ratio (SIR), signal-to-noise ratio (SNR), quality of service for all users or particular classes of users, or individual users, received signal strength intensity (RSSI), throughout, bit error rate (BER), packet error rate (PER), capacity, billing efficiency, etc.) for the wireless or wired network users who are operating within or around the environment.
2. Background Description
As data communications use increases, radio frequency (RF) coverage within and around buildings and signal penetration into buildings from outside transmitting sources has quickly become an important design issue for network engineers who must design and deploy cellular telephone systems, paging systems, wireless or wired computer networks, or new wireless systems and technologies such as personal communication networks or wireless local area networks (WLANs). Similar needs are merging for wireless Internet Service Providers (WISPs) who need to provision and maintain wireless connections to their customers. Designers are frequently requested to determine if a radio transceiver location or base station cell site can provide reliable service throughout an entire city, an office, building, arena or campus. A common problem for wireless networks is inadequate coverage, or a “dead zone” in a specific location, such as a conference room. Such dead zones may actually be due to interference, rather than lack of desired signal. It is understood that an indoor wireless PBX (private branch exchange) system or wireless local area network (WLAN) can be rendered useless by interference from nearby, similar systems.
The costs of in-building and microcell devices which provide wireless coverage are diminishing, and the workload for RF engineers and technicians to install and manage these on-premises systems is increasing sharply. Rapid engineering design, deployment, and management methods for microcell and in-building wireless systems are vital for cost-efficient build-out and on-going operation. The evolving wireless infrastructure is moving toward packet-based transmissions, and outdoor cellular may soon complement in-building Wireless LAN technology. See “Wireless Communications: Past Events and a Future Perspective” by T. S. Rappaport, et al., IEEE Communications Magazine, June 2002 (invited); and “Research Challenges in Wireless Networks: A Technical Overview, by S. Shakkottai and T. S. Rappaport at Proceeding of the Fifth International Symposium on Wireless Personal Multimedia Communications, Honolulu, Hi., October 2002 (invited).
Analyzing and controlling radio signal coverage penetration, network quality of service, and interference is of critical importance for a number of reasons. As more and more wireless networks are deployed in greater capacity, there will be more interference and more management and control needed, which in turn will create a greater need to properly design, measure, and manage, on an on-going basis, the aggregate performance of these networks, using real time autonomous management systems as well as sporadic or periodic adjustments to the wireless infrastructure. Not only will there be a need for properly setting the channels and operating parameters of indoor networks in an optimal or sensible setting upon network turn-on, but real time control will also be needed to guarantee quality of service to different types of wireless users (different class of users), some who may pay a premium for guaranteed data delivery or a more robust form of wireless network access, and other users who may want a lower class of service and who do not wish to pay for premium bandwidth access or who only need intermittent access to the network. Provisioning the Radio Frequency (RF) resources will become more important as users increase and networks proliferate, and scheduling techniques and autonomous control of networks using simpler and more automated and embedded means will be critical for the success and proliferation of ubiquitous wireless networks.
When contemplating a wireless network, such as a Wireless LAN or cellular network to offer service to a group of mobile or portable users, a design engineer must determine if an existing outdoor large-scale wireless system, or macrocell, will provide sufficient coverage and/or capacity throughout a building, or group of buildings (i.e., a campus), or if new hardware is required within the campus. Alternatively, network engineers must determine whether local area coverage will be adequately supplemented by other existing macrocells, or whether and where, particularly, indoor wireless transceivers (such as wireless access points, smart cards, sensors, or picocells) must be added. The placement and configuration of these wireless devices is critical from both a cost and performance standpoint, and the on-going maintenance and management of the network and the management of the performance of users on the network is vital to ensure network quality, quality of service (QoS) requirements, as well as reliability of the wireless network as more users come on the network or install nearby networks.
If an indoor wireless system currently exists, and a new network in a nearby building, home, or urban area is suddenly installed by an unintended interfering neighbor (or worse yet, by an intentional or hostile jammer), there is clearly a need to adapt the network to properly avoid the interference and to maintain network quality. Adaptive techniques such as power control, adaptive antennas, and frequency hopping are well known and have been used for over a decade in the cellular radio and military radio communities. Some literature on the subject includes “Smart Antennas” by Liberti and Rappaport,” Prentice-Hall, c. 1999, and “Wireless Communications: Principles and Practice” (2/e) by T. S. Rappaport, c. 2002.
Not only must judicious planning be done to prevent new wireless indoor networks from interfering with signals from an outdoor macrocell or other nearby indoor networks at the onset of network deployment, but the designer must currently predict how much interference can be expected and where it will manifest itself within the building, or group of buildings ahead of time the best he or she can. Also, providing a wireless system that minimizes equipment infrastructure cost as well as installation cost is of significant economic importance.
It should be clear that a rapid and adaptive method for properly determining operating characteristics of a multiple-transmitter network (such as a Wireless LAN with many access points across a campus) is not only needed in the original installation and start-up of a network, but that in addition, after a system or network is installed, there is a continued need to manage the installed network over time and space, on both an adaptive, real-time or near real time basis through adaptive control, as well as on an intermittent or periodic basis, so that managers, technicians, network owners, and building owners, home owners, etc. are able to record, monitor, and continually ensure proper network operation. At the same time, these individuals need to be able to properly document the installation, adjust the network performance as required over time, and keep track of maintenance records of the system, as well as track the cost, maintenance repairs, and ongoing performance of the system and the components that make up the system in an orderly manner, so that on-going operational data may be gathered, understood, aggregated and used for further maintenance and build-out of wireless networks and systems by those same parties. Even better would be an autonomous system that could automatically conduct such operational bookkeeping so that an indoor wireless network could constantly adapt to the growing and changing interference or environmental changes around it, without the homeowner or building owner even needing to be aware of the operational details.
Research efforts by many leading programs have attempted to model and predict radio wave propagation. Work by AT&T Laboratories, Brooklyn Polytechnic, and Virginia Tech are described in papers and technical reports entitled: S. Kim, B. J. Guarino, Jr., T. M. Willis III, V. Erceg, S. J. Fortune, R. A. Valenzuela, L. W. Thomas, J. Ling, and J. D. Moore, “Radio Propagation Measurements and Predictions Using Three-dimensional Ray Tracing in Urban Environments at 908 MHZ and 1.9 GHz,” IEEE Transactions on Vehicular Technology, vol. 48, no. 3, May 1999 (hereinafter “Radio Propagation”); L. Piazzi, H. L. Bertoni, “Achievable Accuracy of Site-Specific Path-Loss Predictions in Residential Environments,” IEEE Transactions on Vehicular Technology, vol. 48, no. 3, May 1999 (hereinafter “Site-Specific”); G. Durgin, T. S. Rappaport, H. Xu, “Measurements and Models for Radio Path Loss and Penetration Loss In and Around Homes and Trees at 5.85 GHz,” IEEE Transactions on Communications, vol. 46, no. 11, November 1998; T. S. Rappaport, M. P. Koushik, J. C. Liberti, C. Pendyala, and T. P. Subramanian, “Radio Propagation Prediction Techniques and Computer-Aided Channel Modeling for Embedded Wireless Microsystems,” ARPA Annual Report, MPRG Technical Report MPRG-TR-94-12, Virginia Tech, July 1994; T. S. Rappaport, M. P. Koushik, C. Carter, and M. Ahmed, “Radio Propagation Prediction Techniques and Computer-Aided Channel Modeling for Embedded Wireless Microsystems,” MPRG Technical Report MPRG-TR-95-08, Virginia Tech, July 1994; T. S. Rappaport, M. P. Koushik, M. Ahmed, C. Carter, B. Newhall, and N. Zhang, “Use of Topographic Maps with Building Information to Determine Antenna Placements and GPS Satellite Coverage for Radio Detection and Tracking in Urban Environments,” MPRG Technical Report MPRG-TR-95-14, Virginia Tech, September 1995; T. S. Rappaport, M. P. Koushik, M. Ahmed, C. Carter, B. Newhall, R. Skidmore, and N. Zhang, “Use of Topographic Maps with Building Information to Determine Antenna Placement for Radio Detection and Tracking in Urban Environments,” MPRG Technical Report MPRG-TR-95-19, Virginia Tech, November 1995; S. Sandhu, M. P. Koushik, and T. S. Rappaport, “Predicted Path Loss for Roslyn, Va., Second set of predictions for ORD Project on Site Specific Propagation Prediction,” MPRG Technical Report MPRG-TR-95-03, Virginia Tech, March 1995, T. S. Rappaport, et al., “Indoor Path Loss Measurements for Homes and Apartments at 2.4 and 5.85 GHz, by Wireless Valley Communications, Inc., Dec. 16, 1997; Russell Senate Office Building Study, Project Update, Roger R. Skidmore, et al., for Joseph R. Loring & Associates; “Assessment and Study of the Proposed Enhancements of the Wireless Communications Environment of the Russell Senate Office Building (RSOB) and Associated Utility Tunnels,” AoC Contract # Acbr96088, prepared for Office of the Architect of the Capitol, Feb. 20, 1997; “Getting In,” R. K. Morrow Jr. and T. S. Rappaport, Mar. 1, 2000, Wireless Review Magazine; and “Isolating Interference,” by T. S. Rappaport, May 1, 2000, Wireless Review Magazine, “Site Specific Indoor Planning” by R. K. Morrow, Jr., March 1999, Applied Microwave and Wireless Magazine, “Predicting RF coverage in large environments using ray-beam tracing and partitioning tree represented geometry,” by Rajkumar, et al, Wireless Networks, Volume 2, 1996.
The aforementioned papers and technical reports are illustrative of the state-of-the-art in site-specific radio wave propagation modeling. While most of the above papers describe a comparison of measured versus predicted RF signal coverage, or describe methods for representing and displaying predicted performance data, they do not report a comprehensive method for optimizing or adjusting the parameters of equipment settings such as power levels, channelization, or data rates, etc. within an environment to affect a desired behavior in an actual operating network or a planned network.
Furthermore, the above mentioned propagation papers do not teach a way to autonomously allow a network to be properly provisioned for the allocation of multiple classes of data users in a wireless network, nor do they teach any type of display of such performance or the comparisons of predicted versus measured performance that would be due to proper feedback of predicted performance results to the operational wireless infrastructure. While other prior art listed below considers network adaptive control and feedback based on simulation or preset specifications, no work has considered using a site-specific wireless environmental model, that allows a user to simultaneously view the physical environment, control network performance parameters, and see the performance of the network in an adaptive manner.
Additionally, no one has considered the importance of properly configuring, regulating, or controlling the wireless infrastructure in order to properly provision various classes of simultaneous wireless data users in an in-building network, where accurate site-specific propagation modeling is at the heart of driving and setting operating points of an in-building network, so that proper ongoing performance can be carried out in real-time or near real-time as the network changes over time and space. Clearly, this is crucial for on-going network performance as more users and more interfering networks proliferate.
The “Radio Propagation” and “Site-Specific” papers make reference to 3-D modeling, but do not offer novel methods for utilizing the 3-D modeling to carry out automatic equipment configurations or parameter adjustments, nor do they contemplate any type of autonomous control or feedback that uses the predictions to drive, in real time, the actual network performance. An effective method that allows a network communications technician or designers or building owners to automatically determine and visualize the proper configuration and settings of wireless or wired hardware equipment in a site-specific data management system, in a real time or simulated manner, in order to attain optimal or preset desired network performance criteria does not exist in the prior art.
Common to all wireless network and communication system designs as well as wired network designs is the desire to maximize the performance and reliability of the system while minimizing the deployment costs and maximizing on-going performance. Ways to minimize cost include the use of computer aided design tools that manage many aspects of the design process upon installation, and on a periodic basis after the network is operational. Such tools also help create methods that enable the engineer or technician to work quickly and to document their work for others in the organization (SitePlanner and LANPlanner are applications by Wireless Valley Communications, Inc. that provide these capabilities).
Consider a wireless network, for example. Analyzing radio signal coverage, quality of service, capacity, handoff or coverage zones, throughput, delay, signal strength or interference is of critical importance for a number of reasons. A design engineer must determine if an indoor environment that is a candidate for a wireless system contains too much noise or interference, or if the existing wireless system will provide sufficient signal power throughout the desired service area. Alternatively, wireless engineers must determine whether local area coverage will be adequately supplemented by existing large-scale outdoor wireless systems, or macrocells, or whether indoor wireless transceivers, WLAN access points, repeaters, or picocells, must be added. The ability to have adaptive control of the in-building access points so that they can be adjusted automatically in response to changes in the environment to provide improved performance in the face of interference or increased capacity or added users is a significant improvement. Even something as simple as adjusting the carrier frequency or channel of an access point to avoid a nearby jamming access point, adjusting the transmit power of an access point to increase or decrease the coverage area, adjusting the orientation or configuration of electrically steerable or smart antennas, or to throttle down the data rate because of microwave oven interference, could provide significant benefit to users of the network.
The placement and configuration of wireless and wired equipment, such as routers, hubs, switches, cell sites, cables, antennas, distribution networks, receivers, transceivers, transmitters, repeaters, or access points is critical from both a cost and performance standpoint. The design engineer must predict how much interference can be expected from other wireless systems and where it will manifest itself within the environment. In many cases, the wireless network interferes with itself, forcing the designer to carefully analyze many different equipment configurations in order to achieve proper performance. Sometimes power cabling is only available at limited places in a building or campus, thus decisions must be made with respect to the proper location and quantity of access points, and their proper channel assignments. Prediction methods which are known and which are available in the literature provide well-accepted methods for computing coverage or interference values for many cases.
Depending upon the design goals or operating preferences, the performance of a wireless communication system may involve tradeoffs or a combination of one or more factors. For example, the total area covered in adequate received or radio signal strength (RSSI), the area covered with adequate data throughput levels, and the numbers of customers that can be serviced by the system at desired qualities of service or average or instantaneous bandwidth allocations are among the deciding factors used by design engineers in planning the placement of communication equipment comprising the wireless system, even though these parameters change with time and space, as well as with the number and types of users and their traffic demands.
Until the current invention, an adaptive control environment based on site-specific performance prediction modeling for digital data networks, while relying upon real-time wireless network feedback and visual display capabilities for a performance basis, did not exist.
There are many computer aided design (CAD) products on the market that can be used to aid in some manner for wireless design or optimization, but none consider the in-building data scenario with site-specific control and autonomous feedback for network provisioning and scheduling in and around buildings and campuses. WiSE from Lucent Technology, Inc., SignalPro from EDX (now part of Comarco), PLAnet by Mobile Systems International, Inc., (later known as Metapath Software International, now part of Marconi, P. L. C.), decibelPlanner from Marconi, and TEMS from Ericsson, Wizard by Safco Technologies, Inc. (now part of Agilent Technologies, Inc.), are examples of CAD products developed to aid in the design of wireless communication systems.
Agilent Technologies offers Wizard as a design tool for wireless communication systems. The Wizard system predicts the performance of macrocellular wireless communication systems based upon a computer model of a given environment using statistical, empirical, and deterministic predictive techniques.
Lucent Technologies, Inc., offers WiSE as a design tool for wireless communication systems. The WiSE system predicts the performance of wireless communication systems based on a computer model of a given environment using a deterministic radio coverage predictive technique known as ray tracing.
EDX offers SignalPro as a design tool for wireless communication systems. The SignalPro system predicts the performance of wireless communication systems based on a computer model of a given environment using a deterministic RF power predictive technique known as ray tracing.
WinProp offers a Windows-based propagation tool for indoor network planning made by AWE from Germany, and CINDOOR is a European university in-building design tool.
Marconi, P. L. C., offers both PLAnet and decibelPlanner as design tools for wireless communication systems. The PLAnet and decibelPlanner systems predict the performance of macrocellular and microcellular wireless communication systems based upon a computer model of a given environment using statistical, empirical, and deterministic predictive techniques. PLAnet also provides facilities for optimizing the channel settings of wireless transceivers within the environment, but does not provide for further adaptive transceiver configurations beyond channel settings.
Ericsson Radio Quality Information Systems offers TEMS as a design and verification tool for wireless communication indoor coverage. The TEMS system predicts the performance of indoor wireless communication systems based on a building map with input base transceiver locations and using empirical radio coverage models. Teleworx developed an Automatic Frequency Planning Tool (AFP) as announced in January 1999 Wireless Review Magazine, and other corporations such as CelPlan and Safco have implemented Automated Frequency Planning that iteratively determines good channel assignments for transmitters in cellular radio systems.
The above-mentioned design tools have aided wireless system designers by providing facilities for predicting the performance of wireless communication systems and displaying the results primarily in the form of flat, two-dimensional grids of color or flat, two-dimensional contour regions. None of the aforementioned design tools have an automated facility for determining the ideal configurations or establishing pre-set operating points for wireless LAN transceivers or other data-centric modems modeled in a site-specific environment in order to achieve some optimal or desired overall or individual network performance. Furthermore, none of the aforementioned design tools contemplate an automated facility for determining the ideal configurations for wireless data transceivers modeled in a 3-D environment in order to achieve some optimal network performance, while simultaneously displaying the physical location of network assets on a site-specific model of the physical environment.
In addition to the aforementioned design tools, there are several commercially available products that provide the facility for determining optimal transceiver channel settings. Optimizer™ from Schema Ltd., ScoreBoard™ from ScoreBoard Inc., OPAS32 from Agilent Technologies, and E-NOS from Actix are representative of the state-of-the-art in wireless network optimization from the standpoint of frequency planning primarily in the cellular and PCS environments.
Schema Ltd. provides the Optimizer™ software application to assist in the planning and allocation of channels among a specified set of transceivers on a given wireless network. Optimizer™ utilizes measurement information collected either from mobile receivers roaming throughout the coverage area of an existing network or measurement information obtained through monitoring traffic from each transceiver of an existing network. By analyzing the measurement information, Optimizer™ attempts to determine the optimal allocation of channels and/or frequencies across all transceivers participating in the analysis in order to improve the performance of the network. Optimizer™, however, does not consider the physical environment or the detailed specifications or site-specific placements or interconnections of equipment involved in the network, thereby failing to offer the added benefit of visualization of network configuration (valuable for design, deployment, and on-going maintenance, since indoor wireless antennas are often hidden), and further suffering from less accurate modeling since site-specific data is not used by the application. In addition, because Optimizer™ requires measurement data from an existing network, it is not applicable to networks being planned and not yet deployed.
ScoreBoard Inc. provides ScoreBoard™, a comprehensive software solution that assists in the planning and allocation of channels or frequencies among a specified set of transceivers on a given wireless network. ScoreBoard utilizes measurement information collected either from mobile receivers roaming throughout the coverage area of an existing network or measurement information obtained through monitoring traffic reported by transceivers in an existing network. By analyzing the measurement information, ScoreBoard attempts to determine the optimal allocation of channels and/or frequencies across all transceivers participating in the analysis in order to improve the performance of the network. ScoreBoard™, however, does not consider the physical environment or the detailed specifications or site-specific placements or interconnections of equipment involved in the network, thereby failing to offer the added benefit of visualization of network configuration (valuable for design, deployment, and on-going maintenance since indoor network components such as antennas are often hidden), and further suffering from less accurate modeling since site-specific propagation or environmental data is not used by the application. In addition, because ScoreBoard™ requires measurement data from an existing network, it is not as applicable to networks being planned and not yet deployed.
Agilent Technologies provides OPAS32, analysis software that assists in the planning and allocation of channels among a specified set of transceivers on a given wireless network. OPAS32 utilizes measurement information collected from mobile receivers roaming throughout the coverage area of an existing network. By analyzing the measurement information, OPAS32 attempts to determine the optimal allocation of channels and/or frequencies across all transceivers participating in the analysis in order to improve the performance of the network. OPAS32, however, does not consider the physical environment or the detailed specifications or site-specific placements or interconnections of equipment involved in the network, thereby failing to offer the added benefit of visualization of network configuration (valuable for design and on-going maintenance), and further suffering from less accurate modeling since site-specific data is not used by the application. In addition, because OPAS32 requires measurement data from an existing network, it is not applicable to networks being planned and not yet deployed.
Actix provides the E-NOS™ analysis software that assists in the planning and allocation of channels among a specified set of transceivers in a given wireless network. E-NOS™ utilizes measurement information collected from mobile receivers roaming throughout the coverage area of an existing network. By analyzing the measurement information, E-NOS™ attempts to determine the optimal allocation of channels and/or frequencies across all transceivers participating in the analysis in order to improve the performance of the network. E-NOS™, however, does not consider the physical environment or the detailed specifications or site-specific placements or interconnections of equipment involved in the network, thereby failing to offer the added benefit of visualization of network configuration (valuable for design and on-going maintenance), and further suffering from less accurate modeling since site-specific data is not used by the application. In addition, because E-NOS™ requires measurement data from an existing network, it is not applicable to networks being planned and not yet deployed.
Visionael is a network management software company that provides auditing and documentation capabilities for wired data communication networks. Visionael does not use site-specific environmental information or wireless prediction methods for predicting or measuring network performance, nor do they provide support for predicting, measuring, optimizing or controlling parameters that are fundamental to wireless networks. Furthermore, they do not provide means for controlling a wide range of wireless network users for desired performance throughout a network.
In addition, various systems and methods are known in the prior art with the regard to the identification of the location of mobile resources or clients currently roaming on a wireless network. Such systems and methods are generally referred to as position location techniques, and are well-known in the field for their ability to use the RF characteristics of the transmit signal to or from a mobile device as a determining factor for the position of the mobile device. Various papers such as P. Bahl, V. Padmanabhan, and A. Balachandran, “A Software System for Locating Mobile Users: Design, Evaluation, and Lessons,” April 2000, present various techniques for doing position location. The present invention provides significant benefit to the field of position location by enabling the a priori determination of the RF propagation and channel environment within the facility without the need for exhaustive measurement campaigns. The predictive capability of the invention enables the RF channel characteristics—a vital factor in position location algorithms and techniques—to be determined very quickly and accurately. The measurement capability of the invention allows signal measurements to be made from portable client users. The predictive and measurement results can be processed and then be mapped onto a site-specific model of the environment for ready use in carrying out position location displays, and studies or analysis of location-specific data.